References
Arun R., Suresh V., Veni Madhavan C.E. and Narasimha Murthy M.N. (2010). On finding the natural number of topics with latent dirichlet allocation: Some observations. In
Mohammed J. Zaki, Jeffrey Xu Yu, B. Ravindran, and Vikram Pudi, editors, Advances in Knowledge Discovery and Data Mining, pages 391-402, Berlin, Heidelberg. Springer
Berlin Heidelberg.
Benzécri J.P. (1982). Histoire et préhistoire de l’analyse des données. Dunod, Paris.
Blei D.M., Ng A.Y. and Jordan M.I. (2003). Latent dirichlet allocation. Journal of machine Learning research, 3(Jan):993-1022.
Bolasco S. Morrone A. and Baiocchi F. (1999). A Paradigmatic Path for Statistical Content Analysis Using an Integrated Package of Textual Data Treatment, in M. Vichi, O.
Opitz (eds.), Classification and Data Analysis. Theory and Application, Springer-Verlag, Heidelberg, 237-246.
Callon M., Courtial J.-P., Turner W.A. and Bauin S. (1983). From translations to problematic networks: An introduction to co-word analysis. Social science information,
22(2):191-235.
Cao J., Xia T., Li J., Zhang Y. and Tang S. (2009). A density-based method for adaptive lda model selection. Advances in Machine Learning and Computational Intelligence.
Neurocomputing, 72(7):1775-1781.
Demsar J., Curk T., Erjavec A., Gorup C., Hocevar T., Milutinovic M., Mozina M., Polajnar M., Toplak M., Staric A., Stajdohar M., Umek L., Zagar L., Zbontar J., Zitnik M. and
Zupan B. (2013). Orange: Data Mining Toolbox in Python, Journal of Machine Learning Research 14(Aug): 2349-2353.
Deveaud R., Sanjuan E. and Bellot P. (2014). Accurate and effective latent concept modeling for ad hoc information retrieval. Document numérique, 17:61-84, 06.
Devlin J., Chang M.W., Lee K. and Toutanova K. (2018). Bert: Pre-training of deep bidirectional transformers for language understanding. arXiv preprint arXiv:1810.04805.
Fortunato S. and Hric D. (2016). Community detection in networks: A user guide. Physics Reports, 659:1-44, nov.
Giannakidou, A. (2012). Negative and positive polarity items. In K. von Heusinger, C. Maienborn, & P. Portner (Eds.), Semantics: An international handbook of natural
language meaning (pp. 1660–1712). Berlin, D: De Gruyter Mouton Vol. 2 of HandBOOKS OF LINGUISTICS AND COMMUNICATION Science.
Griffiths T.L. and Steyvers M. (2004). Finding scientific topics. Proceedings of the National academy of Sciences, 101(suppl 1):5228-5235.
Hinton G.E. (1986). Learning distributed representations of concepts. In Proceedings of the eighth annual conference of the cognitive science society (1), 12.
Hu M. and Liu B. (2004). Mining and summarizing customer reviews. In Proceedings of the Tenth ACM SIGKDD International Conference on Knowledge Discovery and Data
Mining,KDD ’04, 168-177, New York, NY, USA. Association for Computing Machinery.